In this paper, we compare the performance of several machine learning based approaches for the tasks of detecting algorithmically generated malicious ...
Abstract. In this paper, we compare the performance of several machine learning based approaches for the tasks of detecting algorithmically generated ...
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PDF | In this paper, we compare the performance of several machine learning based approaches for the tasks of detecting algorithmically generated.
Sep 18, 2018 · In this paper, we compare the performance of several machine learning based approaches for the tasks of detecting algorithmically generated ...
May 15, 2021 · A classifier trained with a dataset of both benign and malicious DNs is able both to recognize DNs anomalous with respect to known benign names ...
Sep 22, 2020 · Models based on the analysis of domain names detect algorithmically generated domain names by analyzing the differences in the distribution ...
Our results demonstrate exceptional success in both binary classification (classifying a given domain as benign or malicious), and multiclass classification ( ...
Missing: Algorithmically | Show results with:Algorithmically
AGD detection provides a lightweight yet effective solution to the threats imposed by DGA-based malware. For example, the linguistic distance between domain ...
Since domain name-based detection methods mainly aim to detect AGDs, in this paper, AGD detection has the same meaning as domain name-based detection of DGA ...
The malware family attempts to establish communication with C&C server to flood the unsolicited malicious activities. ... classification of these malwares becomes ...